deeplearning

I want to understand the theoretical properties of (deep) neural networks, and how to use these networks in practice. This repository contains my mathematical derivations of learning algorithms (e.g., backprop), simple Python implementations, and example applications (in the form of ipython notebooks). I will continually add to this repository as I keep studying this field.

Examples

Examples for how to use the code can be found in the notebooks folder, in the form of ipython notebooks.

Here we have a t-SNE visualization of the outputs of the hidden units of a multilayer perceptron trained on the MNIST handwritten digits dataset:

The notebook that generates this graph, using code in this repo, is here

Resources

CS231n: Convolutional Neural Networks for Visual Recognition

Deep Learning Tutorials

Pattern Recognition and Machine Learning, Bishop

Pattern Classification, 2nd Edition, Duda, Hart, and Stork